Various linear and non-linear image processing techniques have been extensively employed in radio astronomy, radar, microwave and sonar applications to enhance the signal to noise ratio (dynamic range) and clarity (resolution) of images. Such systems typically have employed a plurality of transducers and/or receivers to create a synthetic aperture having many advantages over a single or filled aperture, but synthetic aperture systems also inherently including significant noise components.
In radio astronomy applications, or interferometry, quite sophisticated non-linear signal processing techniques have been employed to reduce noise and enhance clarity. Among these techniques is deconvolution of the noise component of image data from the valid signal component, and subsequent convolution of the signal components into a synthetic aperture image having greatly reduced noise and sharper resolution. Since radio astronomy is not concerned with real-time observations, quite elegant, although computer-burdensome, signal processing techniques can be employed to produce significant image enhancement. R. Thompson, et al. Interferometry and Synthesis in Radioastronomy, J. Wiley, 1986.
In applications which will benefit from a substantially real-time display of images, particularly of moving targets, the computing burden of conventional radio astronomy signal processing techniques is too great. In my above-identified co-pending application, I have recently adapted and employed certain interferometry signal processing techniques to ultrasonic echographic imaging. These imaging processing techniques, as employed in biomedical ultrasonic imaging, are more fully described in my prior applications identified above, which are incorporated herein by reference.
Noise deconvolution involves taking an original image data set from an array of transducers or receivers, deconvolving or mathematically separating the noise component side lobe data from the true image data using non-linear algorithms. The original or noise-containing data is sometimes referred to as a "dirty" image data set. It is known, for example, that side-by-side transducers or receivers will receive image data from a point source which would produce an image map having side lobes or noise produced by incompleteness of the synthesized aperture. For any array of a plurality of receivers or transducers, therefore, there will be a characteristic beam pattern (power pattern) or "point spread function" for the array. The beam pattern or point spread function is the image which would be sensed by the array if a single point were the only target in the image field; it does not, however, resemble a single point. Since there are a plurality of side-by-side transducers or receivers in the array making up the synthetic aperture, many of the receivers in the array may "see" the point source to some degree and as a result, the image will not be a point, but a spreading and distortion of the point including side lobes. As the image being processed becomes more complex, with multiple valid targets, the effects of side lobe noise become more pervasive and complex, and removal of these noise effects from the image data for the synthesized aperture becomes more important.
The elimination of noise using deconvolution may proceed by selecting the brightest or highest intensity data point on the "dirty map" of the image and then deconvolving this noise from the valid image data by using an algorithm based upon the point spread function or the characteristic beam pattern. Thus, one assumes that for the given brightest point, the side lobes, or noise, inherent to a multiple transducer array, should be removed. All of the data points, other than the brightest point, which would contain noise or side lobe effects from the brightest point, have their respective intensities reduced by an amount determined by the beam pattern or point spread function. The removal of the beam pattern, therefore, has the effect of removing the side lobes from data throughout the map.
Once noise around the brightest data point has been removed, the deconvolution process then proceeds to the next brightest data point in the dirty map, assumes that this next brightest data point is a valid data point and then removes the corresponding beam pattern for such data point from the remainder of the map. This process continues until the intensity of the brightest data point from which the noise is deconvolved reaches a predetermined level, for example, ten percent, of the intensity of the brightest data point in the entire map.
The beam pattern or point spread function is a three-dimensional pattern with the amplitude being the data intensity or the height dimension. The deconvolution process in which the side lobes are removed, therefore, ideally and in radio astronomy is a three-dimensional process.
Radio astronomy, however, has the luxury of not needing to process the signals on a real-time basis since the objects essentially are stationary from the point of view of the receivers. Additionally, substantial computing power can be dedicated to the signal processing task. As used herein, the expression "real-time" shall be understood to mean imaging at a rate of at least about 15 images (complete data maps) per second and preferably between about 30 to about 60 images per second. In some application real-time is considered to be as low as 5 images per second but this would be acceptable only for relatively slow moving targets.
The result in radio astronomy has been that relatively elegant and more accurate algorithms can be employed to accurately subtract the point spread function or beam pattern by deconvolution of the noise from the signal. Thus, three-dimensional CLEAN algorithms can be used, as can three-dimensional hybrid mapping and maximum entropy algorithms. Maximum entropy is generally regarded as being the most accurate algorithm, but is also has the greatest computational burden.
Typically, in ultrasound imaging, images are displayed on a video display terminal in which there are up to 512 lines with 512 pixels per line. A data map will, therefore, include up to 262,144 pixels or data points. In real-time imaging each map is presented 15 to 60 times per second. As will be appreciated, any deconvolution system which scans all the data points prior to making a selection as to the brightest point, will be faced with a computational burden which is substantial and which will make real-time imaging with an apparatus of reasonable cost very difficult.
It is also known, however, that deconvolution processes inherently introduce data into the processed image data set which is not valid or does not actually represent the object being imaged. These processing induced data are known as image processing "artifacts," and while they are far fewer than the noise data which has been eliminated by deconvolution, they degrade the image and particularly image resolution and produce inaccuracies which may compromise interpretation of the image.
As the deconvolution algorithms get more sophisticated and complex, the number and effects of processing artifacts are reduced, but the computational burden and time required are increased. As assumptions, simplifications and less sophisticated algorithms are employed, real-time processing becomes more realistic, but image degradation from processing artifacts becomes more significant.
Radio astronomy imaging routinely employs cross-correlation of data to produce useful data sets prior to deconvolution. While ultrasonic imaging literature suggests application of cross-correlation to ultrasonic imaging, commercially available ultrasonic imaging apparatus has no provision for data cross-correlation. This is particularly important in that one of the significant sources of image noise is the inhomogeneous medium through which image signals pass. In radio astronomy the medium is miles and miles of atmosphere and the distortions or noise produced by the same is called the "near field effect." In ultrasonic imaging the inhomogeneous medium is human tissue, and the distortion or noise produced is referred to in the industry as "phase aberration."
In radio astronomy imaging the near field effect is completely removed by employing closure phases obtained from the cross-correlation data prior to deconvolution of the noise. In ultrasonic imaging various alternative approximations have been employed to try to minimize or reduce near phase aberration. See, e.g., U.S. Pat. Nos. 4,817,614 to Hasler et al. and 4,835,689 to O'Donnell which employ adaptive reduction of phase aberrations. See also, e.g., companion technical articles, O'Donnell et al. "Phase Aberration Measurements in Medical Ultrasound: Human Studies" Ultrasonic Imaging, Vol. 10, pp. 1-11 (1988); O'Donnell et al. "Aberration Correction without the Need for a Beacon Signal", IEEE Ultrasonics Symposium, pp. 833-837 (1988); O'Donnell et al., "Phase-Aberration Correction Using Signals from Point Reflectors and Diffuse Scatterers: Measurement" IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 35, No. 6, pp. 768-774 (1988). See, also, Hayakawa "Multifrequency Echoscopy for Quantitative Acoustical Characterization of Living Tissues" J. Acoustical Society of America, Vol. 69 (6) , pp. 1838-1840 (1981) where an approximation of the attenuation coefficient in human tissue is developed.
In an article by Somer et al., "Real-Time Improvement of both Lateral and Range Resolution by Optical Signal Processing" Ultrasonics Symposium Proceedings, pp. 1002-1005 (1977) an ultrasonic image enhancing process is described in which lateral and axial resolution is improved by using coherent optical filtering. This is an optical approach to achieve an approximate phase aberration correction.
In U.S. Pat. Nos. 4,604,697 and 4,553,437, both to Luthra et al., a hybrid image is produced from the vector addition of amplitude and phase data from an array of transducers at a plurality of frequencies. The overall image is produced by adding partial images. In U.S. Pat. No. 4,586,135 to Matsumoto side lobe reduction is employed utilizing phase data to provide a holographic data set for reconstruction by a synthetic aperture technique.
Auto and cross-correlation also have been suggested in U.S. Pat. No. 4,397,006 to Galbraith to determine digital time domain filter parameters for noise reduction in seismographic teachings.
I have pointed out in my earlier copending application that by using cross-correlation in ultrasonic imaging and combining the same with specific image processing techniques phase aberration can be completely eliminated. Since present commercially available ultrasonic equipment does not include a cross-correlation capability, however, this approach is not currently easily implemented as an ultrasonic image enhancing process, particularly when retro-fitting existing ultrasonic equipment.
Thus, as phase aberration approximations are employed in ultrasonic imaging, the number of processing artifacts is increased.
Still other attempts have been made to enhance the clarity or resolution of ultrasonic images, but only limited success has been achieved. In U.S. Pat. No. 4,478,085 to Sasaki, the thickness of the ultrasonic transducers was varied over the array to try to minimize beam expansion. U.S. Pat. No. 4,470,305 to O'Donnell employs an annular array of ultrasonic transducers and time delayed pulses to simulate a horn transducer having a sharp focus in the near field. Using this system improved focusing can be achieved up to 20 centimeters, but imaging is accomplished at 3 MHz. The improvement in focus at depth is accomplished in the O'Donnell patent by using variable received signal gains to try to reduce the side lobe noise in the images.
In U.S. Pat. No. 4,677,981 to Coursant, improvement in the ultrasonic echographic image focusing is attempted by using polarization characteristics of the ultrasonic transducers. The disadvantage of this approach is the absence of the initial polarization information and a lack of total intensity. This approach adds little to significantly improve dynamic range and resolution of the ultrasonic images.
Variable frequency ultrasonic scanning also has been used, e.g., U.S. Pat. No. 4,442,715 to Brisken et al., and pitch variation is employed in the device of U.S. Pat. No. 4,664,122 to Yano. Doppler shift also has been employed to detect motion of scanned targets, for example, as is taught in U.S. Pat. No. 4,509,525 to Seo.
In a published abstract of a paper that was not given or published, Dr. Nathan Cohen suggested that in underwater acoustic imaging linear and nonlinear imaging techniques could be used to aid in recovery of phase observables for increased dynamic range and image accuracy. The abstract also suggested that techniques from imaging disciplines such as optics and radio astronomy might be applied. Cohen, "Phase Recovery and Calibration with Underwater Acoustic Arrays", J. Acoustical Society of America, Sup. 1, Vol. 82, pp. 574-575 (1987). The techniques which might be applicable, how they might be applied and their suitability for medical imaging is not set forth in the abstract.
While radio astronomy images are displayed in Cartesian coordinates as X.Y images, ultrasonic images are more conventionally displayed in polar coordinates. Thus, a sector-like ultrasonic image is displayed in which the apex of the image is located at the transducer array. The data are displayed in a range or radius, r, and an azimuth or angle, .theta., format.
When an r,.theta. display format is used, the noise and side lobes at increasing range from the transducer will appear larger in extent. The image at increasing ranges appears much noisier than at ranges close to the transducer. In order to deconvolve the beam noise for an r,.theta. format display, a coordinate transformation of the r,.theta. data to X,Y coordinates for deconvolution in the X,Y format usually is performed. It also would be possible to convert the X,Y point spread function into r,.theta. format and then deconvolve the noise and in an r,.theta. format for conventional display.
The process and apparatus set forth in my prior copending application does not eliminate noise in the form of signal processing artifacts, nor is phase aberration reduced for signal processing equipment which does not include a cross-correlator. Both these goals are highly desirable, particularly if they can be accomplished at real-time rates with apparatus which can be retrofit to existing equipment at only modest cost.
Accordingly, it is an object of the present invention to provide an image processing method and apparatus which is capable of substantially reducing and even eliminating image processing artifacts produced by nonlinear and linear image processing techniques.
It is a further object of the present invention to provide an image processing method and apparatus which is capable of producing images having enhanced dynamic range and only a modest increase in computational burden.
It is another object of the present invention to provide an echography apparatus and method which will generate high-resolution images, at real-time imaging rates, of stationary and moving target objects in an inhomogeneous medium using ultrasonic signals.
Still a further object of the present invention is to provide an ultrasonic imaging apparatus and method which can retrofit to and is usable with existing ultrasonic transducer arrays and correlators to enhance the resolution and dynamic range of the images produced.
Still another object of the present invention is to provide an image processing apparatus and method in which phase aberration can be reduced.
Another object of the present invention is to provide an echographic image processing apparatus and method which is capable of real-time image processing with reduced phase aberration and reduced processing-induced noise, and which has modest cost and can be easily retrofit for use with a variety of echographic imaging apparatus.
Still another object of the present invention is to provide an image processing apparatus and method which can be easily adjusted by medical personnel to empirically reduce phase aberration.
The apparatus and method of the present invention have other features of advantage and objects which will become apparent from, and are set forth in more detail in the following Best Mode of Carrying Out the Invention and the accompanying drawing.